Mitochondrial Aldehyde Dehydrogenase 2 Represents a Potential Biomarker of Biochemical Recurrence in Prostate Cancer Patients

Identification of circadian clock-related immunological prognostic index and molecular subtypes in prostate cancer

BACKGROUND

Evidence suggests that the circadian clock (CIC) is among the important factors for tumorigenesis. We aimed to provide new insights into CIC-mediated molecular subtypes and gene prognostic indexes for prostate cancer (PCa) patients undergoing radical prostatectomy (RP) or radical radiotherapy (RT).

METHODS

PCa data from TCGA was analyzed to identify differentially expressed genes (DEGs) with significant fold changes and p-values. A prognostic index called CIC-related gene prognostic index (CICGPI) was developed through clustering methods and survival analysis and validated on multiple data sets. The diagnostic accuracy of CICGPI for resistance to chemotherapy and radiotherapy was confirmed. Additionally, the interaction between tumor immune environment and CICGPI score was explored, along with their correlation with prognosis.

RESULTS

TOP2A, APOE, and ALDH2 were used to classify the PCa patients into two subtypes. Cluster 2 had a higher risk of biochemical recurrence (BCR) than cluster 1 for PCa patients undergoing RP or RT. A CIC-related gene prognostic index (CICGPI) was constructed using the above three genes for PCa patents in the TCGA database. The CICGPI score showed good prognostic value in the TCGA database and was externally confirmed by PCa patients in GSE116918, MSKCC2010 and GSE46602. In addition, the CICGPI score had a certain and high diagnostic accuracy for tumor chemoresistance (AUC: 0.781) and radioresistance (AUC: 0.988). For gene set variation analysis, we observed that both beta alanine metabolism and limonene and pinene degradation were upregulated in cluster 1 for PCa patients undergoing RP or RT. For PCa patients undergoing RP, cell cycle, homologous recombination, mismatch repair, and DNA replication were upregulated in cluster 2. A strongly positive relationship between cancer-related fibroblasts and CICGPI score was observed in PCa patients undergoing RP or RT. Moreover, a high density of CAFs was highly closely associated with poorer BCR-free survival of PCa patients.

CONCLUSIONS

In this study, we established CIC-related immunological prognostic index and molecular subtypes, which might be useful for the clinical practice.

ALDH2 is a novel biomarker and exerts an inhibitory effect on melanoma

Melanoma is a malignant skin tumor. This study aimed to explore and assess the effect of novel biomarkers on the progression of melanoma. Differently expressed genes (DEGs) were screened from GSE3189 and GSE46517 datasets of Gene Expression Omnibus database using GEO2R. Gene Ontology and Kyoto Encyclopedia of Genes and Genomes pathway analyses were conducted based on the identified DEGs. Hub genes were identified and assessed using protein-protein interaction networks, principal component analysis, and receiver operating characteristic curves. Quantitative real-time polymerase chain reaction was employed to measure the mRNA expression levels. TIMER revealed the association between aldehyde dehydrogenase 2 (ALDH2) and tumor immune microenvironment. The viability, proliferation, migration, and invasion were detected by cell counting kit-8, 5-ethynyl-2'-deoxyuridine, wound healing, and transwell assays. Total 241 common DEGs were screened out from GSE3189 and GSE46517 datasets. We determined 6 hub genes with high prediction values for melanoma, which could distinguish tumor samples from normal samples. ALDH2, ADH1B, ALDH3A2, DPT, EPHX2, and GATM were down-regulated in A375 and SK-MEL-2 cells, compared with the human normal melanin cell line (PIG1 cells). ALDH2 was selected as the candidate gene in this research, presenting a high diagnostic and predictive value for melanoma. ALDH2 had a positive correlation with the infiltrating levels of immune cells in melanoma microenvironment. Overexpression of ALDH2 inhibited cell viability, proliferation, migration, and invasion of A375/SK-MEL-2 cells. ALDH2 is a new gene biomarker of melanoma, which exerts an inhibitory effect on melanoma.

Aldehyde dehydrogenase 2-mediated aldehyde metabolism promotes tumor immune evasion by regulating the NOD/VISTA axis

BACKGROUND

Aldehyde dehydrogenase 2 (ALDH2) is a crucial enzyme involved in endogenous aldehyde detoxification and has been implicated in tumor progression. However, its role in tumor immune evasion remains unclear.

METHODS

Here, we analyzed the relationship between ALDH2 expression and antitumor immune features in multiple cancers. ALDH2 knockout tumor cells were then established using CRISPR/Cas9 system. In immunocompetent breast cancer EMT6 and melanoma B16-F10 mouse models, we investigated the impact of ALDH2 blockade on cytotoxic T lymphocyte function and tumor immune microenvironment by flow cytometry, mass cytometry, Luminex liquid suspension chip detection, and immunohistochemistry. Furthermore, RNA sequencing, flow cytometry, western blot, chromatin immunoprecipitation assay, and luciferase reporter assays were employed to explore the detailed mechanism of ALDH2 involved in tumor immune evasion. Lastly, the synergistic therapeutic efficacy of blocking ALDH2 by genetic depletion or its inhibitor disulfiram in combination with immune checkpoint blockade (ICB) was investigated in mouse models.

RESULTS

In our study, we uncovered a positive correlation between the expression level of ALDH2 and T-cell dysfunction in multiple cancers. Furthermore, blocking ALDH2 significantly suppressed tumor growth by enhancing cytotoxic activity of CD8+ T cells and reshaping the immune landscape and cytokine milieu of tumors in vivo. Mechanistically, inhibiting ALDH2-mediated metabolism of aldehyde downregulated the expression of V-domain Ig suppressor of T-cell activation (VISTA) via inactivating the nucleotide oligomerization domain (NOD)/nuclear factor kappa-B (NF-κB) signaling pathway. As a result, the cytotoxic function of CD8+ T cells was revitalized. Importantly, ALDH2 blockade markedly reinforced the efficacy of ICB treatment.

CONCLUSIONS

Our data delineate that ALDH2-mediated aldehyde metabolism drives tumor immune evasion by activating the NOD/NF-κB/VISTA axis. Targeting ALDH2 provides an effective combinatorial therapeutic strategy for immunotherapy.

Identification of a novel senescence-associated signature to predict biochemical recurrence and immune microenvironment for prostate cancer

Background

Prostate cancer (PCa) is an age-associated malignancy with high morbidity and mortality rate, posing a severe threat to public health. Cellular senescence, a specialized cell cycle arrest form, results in the secretion of various inflammatory mediators. In recent studies, senescence has shown an essential role in tumorigenesis and tumor development, yet the extensive effects of senescence in PCa have not been systematically investigated. Here, we aimed to develop a feasible senescence-associated prognosis model for early identification and appropriate management in patients with PCa.

Method

The RNA sequence results and clinical information available from The Cancer Genome Atlas (TCGA) and a list of experimentally validated senescence-related genes (SRGs) from the CellAge database were first obtained. Then, a senescence-risk signature related with prognosis was constructed using univariate Cox and LASSO regression analysis. We calculated the risk score of each patient and divided them into high-risk and low-risk groups in terms of the median value. Furthermore, two datasets (GSE70770 and GSE46602) were used to assess the effects of the risk model. A nomogram was built by integrating the risk score and clinical characteristics, which was further verified using ROC curves and calibrations. Finally, we compared the differences in the tumor microenvironment (TME) landscape, drug susceptibility, and the functional enrichment among the different risk groups.

Results

We established a unique prognostic signature in PCa patients based on eight SRGs, including CENPA, ADCK5, FOXM1, TFAP4, MAPK, LGALS3, BAG3, and NOX4, and validated well prognosis-predictive power in independent datasets. The risk model was associated with age and TNM staging, and the calibration chart presented a high consistency in nomogram prediction. Additionally, the prognostic signature could serve as an independent prediction factor due to its high accuracy. Notably, we found that the risk score was positively associated with tumor mutation burden (TMB) and immune checkpoint, whereas negatively correlated with tumor immune dysfunction and exclusion (TIDE), suggesting that these patients with risk scores were more sensitive to immunotherapy. Drug susceptibility analysis revealed differences in the responses to general drugs (docetaxel, cyclophosphamide, 5-Fluorouracil, cisplatin, paclitaxel, and vincristine) were yielded between the two risk groups.

Conclusion

Identifying the SRG-score signature may become a promising method for predicting the prognosis of patients with PCa and tailoring appropriate treatment strategies.